Whisper Transcribe
PYPI · WHISPER-TRANSCRIBE-MCP
Transcribe audio locally with faster-whisper or through the OpenAI Whisper API.
Available components
Last scanned (23 hours ago)
Scores higher than 94% of PyPI servers
Category AI and Machine Learning
How this component scores in each security and reliability category. Every signal is checked automatically from public evidence about the published package, including repeated runs of it in an isolated sandbox, and we only credit what we can confirm. How we score → Why this is hard to score →
Supply Chain Security100
- No malware found by supply-chain analysis.Pass
- No known CVEs affecting this package version or its production dependencies.Pass
- Runs hatchling.build at install time, a recognised build step with no custom scripting around it. View diagnostics → Pass
- 2 of 37 dependencies flagged as unhealthy. View diagnostics → Partial
Provenance & Transparency97
- Source repository is publicly reachable at the declared URL. View diagnostics → Pass
- Cryptographically verified build provenance (signed, bound to ZahiriNatZuke/whisper-transcribe-mcp). View diagnostics → Pass
- Clear OSI-approved license (MIT).Pass
- Actively maintained (last published 42 days ago).Pass
- Disclosure check failed: no security disclosure policy was found in the source repository. See how to fix → Fail
Schema Quality & AI Usability78
- AI-judged instruction clarity (excellent).Pass
- Tool/resource definitions use about 398 tokens (~132/item across 3 items; 3 tools + 0 resources), lean.Pass
- Usage-examples check failed: none of the tools include examples. See how to fix → Fail
Stability & Change Management67
- Stability observed for 20 of 30 days with no destabilising changes; credit accrues until the full window elapses.Partial
Tool Coverage100
- 100% of tools have a non-trivial description (not blank, and not just the tool's name).Pass
- 100% of tool parameters carry a description.Pass
- Structured output schemas are declared (100% of tools); any adoption earns full credit.Pass
Tool Safety100
- No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.Pass
- We read all 3 captured tool definition(s), and no name or description among them implies an irreversible operation.Pass
- An AI judge read all 3 captured unit(s) of tool text and found none that tries to manipulate the model reading it.Pass
Capabilities100
- Implements a current MCP spec version (2026-07-28).Pass
Every change we have recorded for this component, newest first. Security-relevant changes are always shown. ▲ marks a change for the better, ▼ a change for the worse; unmarked changes are neutral.
- 4 Nov 26 −4
- Stability: pass → 0.67 functional
- 29 Oct 26 +15
- Malware scan: unverified → pass ▲ security
- Stability: 0.97 → pass security
- 28 Oct 26 0
- Stability: pass → 0.97 functional
- 18 Oct 26 −15
- Malware scan: pass → unverified ▼ security
- 17 Oct 26 +15
- Malware scan: unverified → pass ▲ security
- 16 Oct 26 0
- Stability: 0.97 → pass security
- 15 Oct 26 +46
- Injection markers: unverified → pass ▲ security
- Stability: unverified → 0.97 ▲ functional
- Tool coverage: unverified → 100 ▲ functional
- MCP protocol: unverified → pass ▲ functional
- 14 Oct 26 −15
- Malware scan: pass → unverified ▼ security
Diagnostic detail from the automated scan of this channel: what the scanner observed at each step, so you can see exactly where a check passed or failed. It is informational only and never changes the trust score.
Captured 4 Nov 2026 · Analysed pypi/whisper-transcribe-mcp@1.1.3
Provenance Verified
A signed build attestation was found and verified, binding this exact artifact to the source repository it claims to come from.
| Result | Verified |
|---|---|
| Ecosystem | pypi |
| Reason | Verified |
| Discovered via | Registry attestation endpoint |
| Source repo | ZahiriNatZuke/whisper-transcribe-mcp |
| Certificate issuer | https://token.actions.githubusercontent.com |
| Certificate SAN | https://github.com/ZahiriNatZuke/whisper-transcribe-mcp/.github/workflows/publish.yml@refs/tags/v1.1.3 |
| Rekor log index | 2909485791 |
| Predicate type | PyPI publish attestation https://docs.pypi.org/attestations/publish/v1 |
| Subject digest | sha256:6b17d68263c9a759e5840707c97adba2203daa4b8e5a4f22a71a0c71e9d47109 |
Background: How many MCP packages publish verified provenance →
Install scripts 1 script
| Hook | Tier | Command |
|---|---|---|
| build_backend | allowlisted | hatchling.build |
Background: Why install scripts are a supply-chain risk →
Dependencies 37 packages
| Packages resolved | 37 |
|---|---|
| Stale | 1 |
| No linked repository | 1 |
| Tree resolution | Complete |
Background: SBOMs and build attestations, explained →
The tools this component advertises to a client, with an estimated token cost for each. Expand a tool to see its parameters and schema. The per-tool counts are indicative and are not scored directly; the schema's total context footprint is one signal in Schema Quality & AI Usability. A tool's description is untrusted text the model reads on every call, which is what makes this list a security surface and not just an inventory: how tool poisoning works →
list_models List Models ~17
List available Whisper model sizes and current configuration.
Input schema present but exposes no named parameters.
Structured output declared, but exposes no named fields.
No examples provided.
transcribe_base64 Transcribe Base64 ~165
Transcribe audio provided as a base64-encoded string.
| Name | Type | Req | Description |
|---|---|---|---|
| audio_base64 | string | yes | Base64-encoded audio data. |
| extension | string | – | Audio format of the data (mp3, wav, m4a, ogg, flac, webm, mp4, etc.). |
| language | – | – | Language code. Auto-detected if not provided. |
| model_size | – | – | Local model size. Ignored when using the OpenAI backend. |
| post_process | boolean | – | If True, passes the transcription through GPT to fix spelling, grammar, and punctuation. Requires the openai package. |
| post_process_prompt | – | – | Custom system prompt for post-processing. Use this to provide domain-specific context, proper nouns, or product names. |
Structured output declared, but exposes no named fields.
No examples provided.
transcribe_file Transcribe File ~216
Transcribe an audio file to text.
| Name | Type | Req | Description |
|---|---|---|---|
| file_path | string | yes | Absolute path to the audio file (mp3, wav, m4a, ogg, flac, etc.) |
| language | – | – | Language code (e.g. 'es', 'en', 'fr'). Auto-detected if not provided. |
| model_size | – | – | Local model size: tiny, base, small, medium, large-v3 (plus the .en, turbo, and distil variants). Ignored when using the OpenAI backend. Defaults to the WHISPER_MODEL environment vari… |
| post_process | boolean | – | If True, passes the transcription through GPT to fix spelling, grammar, and punctuation. Requires the openai package. |
| post_process_prompt | – | – | Custom system prompt for post-processing. Use this to provide domain-specific context, proper nouns, or product names that Whisper may have misspelled. Falls back to… |
Structured output declared, but exposes no named fields.
No examples provided.
How do I install the Whisper Transcribe MCP server?
Whisper Transcribe runs locally as a PyPI package, launched with uvx whisper-transcribe-mcp. Ready-made configuration for Claude, Cursor, VS Code, Codex and 5 more is on this page, copied from each client's own documentation.
pypi · whisper-transcribe-mcp
claude mcp add zahirinatzuke-whisper-transcribe-mcp -- uvx whisper-transcribe-mcp
What is the Whisper Transcribe MCP server?
Whisper Transcribe is an MCP server listed in the public MCP registry as io.github.ZahiriNatZuke/whisper-transcribe-mcp. Transcribe audio locally with faster-whisper or through the OpenAI Whisper API. This page covers its PyPI package (whisper-transcribe-mcp).
Is the Whisper Transcribe MCP server safe to use?
Whisper Transcribe scores 91 out of 100 on VerifyMCP. We found no known CVEs affecting it as of 4 November 2026. Its build provenance is signed and verified. That is a record of what we were able to check automatically, not an endorsement. The category breakdown on this page shows every signal behind the number, including the ones we could not confirm.
What tools does the Whisper Transcribe MCP server expose?
Whisper Transcribe exposes 3 tools: transcribe_file, transcribe_base64, list_models. Their descriptions and schemas cost roughly 398 tokens of context every time the server is loaded.
Is the Whisper Transcribe MCP server still maintained?
Whisper Transcribe is still listed as active in the MCP registry. We last reached this channel on 4 November 2026. Those dates come from our own scans of the registry and the channel itself, not from anything the publisher announced.
What licence is the Whisper Transcribe MCP server under?
Whisper Transcribe declares the MIT licence, which is OSI-approved. That covers the source only, and says nothing about the cost of any service it calls.